There has been a longstanding need for techniques to detect and identify unknown particles contained in fluid media. One example of such a need is the desire to detect and identify pathogenic microorganisms contained in water. Protozoan parasites such as Cryptosporidium parvum and Giardia lamblia have been recognized as important waterborne etiologic agents of disease after contact with or ingestion of contaminated water. C. parvum is of major concern because it exhibits high resistance to disinfectants at the doses routinely applied in water treatment plants, has a low infectious dose, and no drug is currently approved for prophylaxis or therapy.
Current water quality monitoring techniques for Cryptosporidium and Giardia have well-known and serious limitations. First, standard techniques—from sample collection to final identification and enumeration—can take at least a day. This delay reduces or eliminates health benefits associated with monitoring (M. J. Allen et al., JAWWA, September 2000). Second, these techniques are labor intensive and expensive. Third, samples are often collected discretely; so transient contamination spikes are very likely to be missed by sporadic sampling. Fourth, the accuracy of the identification techniques is unacceptably poor. For example, typical recovery and identification for two standard methods, immuno-fluorescence assay (IFA) and flow cytometry cell sorting (FCCS), is around 40% for Giardia and around 40–50% for Cryptosporidium, with high coefficients of variation and high false positive rates, primarily from benign species such as algae (Comparative Health Effects Assessments of Drinking Water Technologies: Report to Congress, November 1988; M. LeChevallier, JAWWA, September 1995, p. 54; M. Frey, C. Hancock, and G. S. Jackson, AWWARF and AWWA, 1997; J. L. Clancy et al., JAWWA, September 1999).
Attempts to monitor water for the presence and identity of microorganisms by light scattering have met with little success—the difficulty lies in the ability to “invert” the light scattering data to determine what particle did the scattering. The inverse scattering problem is well known in classical electromagnetic theory. Unlike the “forward scattering” problem, in which the scattered radiation is completely predictable based on sufficient information about the scattering particle, the inverse scattering problem is defined by attempting to determine the physical properties of the scattering particle from the scattered radiation. Such physical properties include, for example, size, shape, internal structure, and refractive index.
A well-known solution to the inverse scattering problem is Inverse Synthetic Aperture RADAR. RADAR waves are scattered from a moving target that changes its attitude relative to the RADAR source. Scattered phase and amplitude information is collected, and a RADAR image of the target is reconstructed using signal-processing techniques (c.f. E. F. Knott, J. F. Shaeffer, and M. T. Tuley, Radar Cross Section, Artech House, Inc., Norwood, Mass., 1985. P. 202).
The analogous problem in optics is more problematic, because phase information is difficult to obtain due to the short wavelengths involved. Without phase information, a rigorous analytical reconstruction of the scattering particle, particularly a complex object, such as a microorganism, becomes untenable using standard techniques.
Quist and Wyatt achieved a solution to the optical inverse scattering problem using scattered amplitudes alone in the early 1980's (G. M. Quist and P. J. Wyatt, J. Optical Soc. Am., November 1985, pp. 1979–1985; U.S. Pat. No. 4,548,500). Because this technique relies upon simultaneous measurement of various scattered light angles, the technique is called the Multi-Angle Light Scattering (MALS) technique. Using a scheme called “strip maps,” Quist and Wyatt demonstrated that it is possible to uniquely and rapidly characterize simple particles, such as homogeneous and isotropic spheres, homogeneous rods, and homogeneous ellipsoids, using optical data generated solely from the differential cross section (the angular dependence of the scattering amplitude) without explicit phase information. However, the strip map technique is limited to simple geometric structures.
The MALS technique has been utilized with various microparticles, including, bacteria and flyash, to produce coherent scattered light patterns with multiple nulls. In 1989, Wyatt and Jackson extended the MALS technique to classifying microbiological particles in water (P. J. Wyatt and C. Jackson, Limnology and Oceanography, January 1989, pp. 96–112). They demonstrated that it is possible to classify 12 distinct species of phytoplankton in seawater with a statistical confidence level of greater than 99%.
The problem of waterborne outbreaks of disease related to Giardia and Cryptosporidium, and their presence at the effluent of state-of-the-art water treatment plants complying with current regulations, clearly indicates the importance of effective real time, continuous monitoring systems to identify their presence in water. Thus, it is desirable to develop a method to identify particles in a fluid, with one example being the use of such a method to detect and identify rapidly and accurately Cryptosporidium and Giardia in drinking water.